Hi,
I have data pertaining to Life Insurance Profitability and wanted to measure the same before 2010 and after 2010. Main objective was to prove that regulations passed on after 2010 had impacted profitability.
@Ramesh If your data meet the assumptions of metric test then go for pairedt-test.
I thing that in this case, the groups are dependent according to your explanation, so you must use Paired Sample T Test, not ANOVA, because you are testing the deference between two period in terms of an attribute for the same sample, not the deference in the same period.
1) The first thing to note is that whatever your results are, you can't attribute the difference between pre-2010 and post-2010 to any single cause. If there's a difference, it _could_ be due to the regulations, but it could be due to any one or more of many possible causes. There's nothing in your design to differentiate among these possible causes.
2) You should start by assessing if there is an overall trend in your data over time. If there is a general trend of increasing profitability over time, then a difference between before-2010 and post-2010 could be due to this trend, and there may be no meaningful change at 2010 per se. It would be helpful to investigate the analysis of time-series data to handle this question.
3) There's really not enough information in your question for anyone to suggest what kind of analysis to use. The most important question that comes to mind, is, how many individuals are you looking at? I mean, are you looking at the profitability of one company over time? Or the profitability of the whole industry over time? Or are you looking at the profitability of several companies over time?
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